Apache Pig vs. Cloudera Distribution Hadoop (CDH)

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Pig
Score 8.3 out of 10
N/A
Apache Pig is a programming tool for creating MapReduce programs used in Hadoop.N/A
Cloudera Distribution Hadoop (CDH)
Score 6.9 out of 10
N/A
CDH is Cloudera’s 100% open source platform distribution, including Apache Hadoop and built specifically to meet enterprise demands. CDH delivers everything needed for enterprise use right out of the box. By integrating Hadoop with more than a dozen other critical open source projects, Cloudera has created a functionally advanced system that helps you perform end-to-end Big Data workflows.N/A
Pricing
Apache PigCloudera Distribution Hadoop (CDH)
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Apache PigCloudera Distribution Hadoop (CDH)
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache PigCloudera Distribution Hadoop (CDH)
Top Pros
Top Cons
Best Alternatives
Apache PigCloudera Distribution Hadoop (CDH)
Small Businesses

No answers on this topic

No answers on this topic

Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 9.3 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 9.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache PigCloudera Distribution Hadoop (CDH)
Likelihood to Recommend
8.1
(9 ratings)
7.0
(1 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
6.0
(2 ratings)
-
(0 ratings)
User Testimonials
Apache PigCloudera Distribution Hadoop (CDH)
Likelihood to Recommend
Apache
Apache Pig is best suited for ETL-based data processes. It is good in performance in handling and analyzing a large amount of data. it gives faster results than any other similar tool. It is easy to implement and any user with some initial training or some prior SQL knowledge can work on it. Apache Pig is proud to have a large community base globally.
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Cloudera
Cloudera Distribution Hadoop (CDH) does a lot of things really well - especially on the analytical front. That being said the product is quite expensive. There are seemingly numerous applications that do the same thing on the functional level that are much more cost effecient for enterprise teams. If I were recommending this to a colleague I would let them know the product will absolutely be able to get the job done for their use case, but there are more efficient options
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Pros
Apache
  • Its performance, ease of use, and simplicity in learning and deployment.
  • Using this tool, we can quickly analyze large amounts of data.
  • It's adequate for map-reducing large datasets and fully abstracted MapReduce.
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Cloudera
  • Solid and robust set of integrations
  • Easy to use and easy to deploy across the enterprise
  • Reliability - never lost any info
  • Simple and clean interface
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Cons
Apache
  • UDFS Python errors are not interpretable. Developer struggles for a very very long time if he/she gets these errors.
  • Being in early stage, it still has a small community for help in related matters.
  • It needs a lot of improvements yet. Only recently they added datetime module for time series, which is a very basic requirement.
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Cloudera
  • The price is quite high competitively speaking
  • Hard to learn more robust functions and custom options without experience
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Usability
Apache
It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
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Cloudera
No answers on this topic
Support Rating
Apache
The documentation is adequate. I'm not sure how large of an external community there is for support.
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Cloudera
No answers on this topic
Alternatives Considered
Apache
Apache Pig might help to start things faster at first and it was one of the best tool years back but it lacks important features that are needed in the data engineering world right now. Pig also has a steeper learning curve since it uses a proprietary language compared to Spark which can be coded with Python, Java.
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Cloudera
In terms of functionality there's not much difference, both get the job done. Amazon was more cost-efficient for our team, but this could vary depending on the size of the business. One thing I did notice was that Cloudera seemed to management and spit out our deployments faster than AWS.
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Return on Investment
Apache
  • Higher learning curve than other similar technologies so on-boarding new engineers or change ownership of Apache Pig code tends to be a bit of a headache
  • Once the language is learned and understood it can be relatively straightforward to write simple Pig scripts so development can go relatively quickly with a skilled team
  • As distributed technologies grow and improve, overall Apache Pig feels left in the dust and is more legacy code to support than something to actively develop with.
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Cloudera
  • Saves time by automating typically manual processes (data management, lifecyle AI etc)
  • Quick deployments and analytics allow for faster time-to-value
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ScreenShots